Understanding the impact of test validity and bias on selection errors and adverse impact in human resource selection

We propose an integrative framework for understanding the relationship among 4 closely related issues in human resource (HR) selection: test validity, test bias, selection errors, and adverse impact. One byproduct of our integrative approach is the concept of a previously undocumented source of selection errors we call bias-based selection errors (i.e., errors that arise from using a biased test as if it were unbiased). Our integrative framework provides researchers and practitioners with a unique tool that generates numerical answers to questions such as the following: What are the anticipated consequences for bias-based selection errors of various degrees of test validity and test bias? What are the anticipated consequences for adverse impact of various degrees of test validity and test bias? From a theory point of view, our framework provides a more complete picture of the selection process by integrating 4 key concepts that have not been examined simultaneously thus far. From a practical point of view, our framework provides test developers, employers, and policy makers a broader perspective and new insights regarding practical consequences associated with various selection systems that vary on their degree of validity and bias. We present a computer program available online to perform all needed calculations.